Text, graphic, or line images are often replicated or transmitted by a variety of techniques, such as photocopying, facsimile transmission, and scanning of such images into a memory device. The process of replication or transmission often tends to degrade quality of resulting image due to a variety of factors. Degraded images are characterized by indistinct or shifted edges, blended or otherwise connected characters, and distorted shapes.
A reproduced or transmitted image that is degraded in quality may be unusable in certain applications. For example, if the reproduced or transmitted image is to be used in conjunction with a character recognition apparatus, the indistinct edges and/or connected characters may preclude accurate or successful recognition of text or characters in the image. Also, if the degraded image is printed or otherwise rendered visible, the image may be more difficult to read and less visually distinct.
Various efforts have been made in the past for improving image quality. One such effort involve resolution enhancement algorithm which provides template matching. Template matching attempts to match a line, curve pattern, or linear pattern; and then tries to find the best way to reconstruct it within the available printing resolution.
Shiau et al., U.S. Pat. No. 5,852,678 and related European Patent Application No. EP0810774, disclose method and apparatus that improve digital reproduction of a compound document image containing half-tone tint regions and text and/or graphics embedded within the half-tone tint regions. The method entails determining a local average pixel value for each pixel in the image, then discriminating and classifying based on the local average pixel values, text/graphics pixels from half-tone tint pixels. Discrimination can be effected by calculating a range of local averages within a neighborhood surrounding each pixel; by calculating edge gradients based on the local average pixel values; or by approximating second derivatives of the local average pixel values based on the local averages. Text/graphics pixels are rendered using a rendering method appropriate for that type of pixel. That is, half-tone tint pixels are rendered using a rendering method appropriate for that type of pixel.
Barski et al., U.S. Pat. No. 5,212,741, discloses method and apparatus for processing image data of dot-matrix/ink-jet printed text to perform Optical Character Recognition (OCR) of such image data. In the disclosed method and apparatus, the image data is viewed for detecting if dot-matrix/ink-jet printed text is present. Any detected dot-matrix/ink-jet produced text is then pre-processed by determining the image characteristic thereof by forming a histogram of pixel density values in the image data. A two-dimensional spatial averaging operation as a second pre-processing step smoothes the dots of the texts into strokes and reduces the dynamic range of the image data. The resultant spatially averaged image data is then contrast stretched in a third pre-processing step to darken dark regions of the image data and lighten light regions of the image data. Edge enhancement is then applied to the contrast stretched image data in a fourth pre-processing step to bring out higher frequency line details. The edge enhanced image data is then binarized and applied to a dot-matrix/ink jet neural network classifier for recognizing characters in the binarized image data from a predetermined set of symbols prior to OCR.
The above cited approaches generally teach global techniques aimed at intelligent binarization, OCR, and document image analysis. They do not teach nor suggest local image quality enhancement of text, graphic, or line art. With local image quality enhancement, a skilled person may understand the application of image quality enhancement technique on a particular user-selected image. Hence, there is a need to have an image quality enhancement technique that can detect and enhance text, graphic, or and line art in a given document image.